Instructions to use ania3000/kuosbert-from_multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ania3000/kuosbert-from_multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ania3000/kuosbert-from_multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ania3000/kuosbert-from_multilingual") model = AutoModelForMaskedLM.from_pretrained("ania3000/kuosbert-from_multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a00fc4abbe1d25e0272a08721d32cb6ea647dfef3f8c519946552bf697e791e
- Size of remote file:
- 5.84 kB
- SHA256:
- bf575cbb7523002da82cee8981cd9ade5123ede8c9cdbd165e3604089e1d68b3
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